Correlation and instance based feature selection for electricity load forecasting

    Knowledge-Based Systems, Volume 82, Issue C, 2015, Pages 29-40.

    Cited by: 89|Bibtex|Views16|Links
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    Abstract:

    Appropriate feature (variable) selection is crucial for accurate forecasting. In this paper we consider the task of forecasting the future electricity load from a time series of previous electricity loads, recorded every 5min. We propose a two-step approach that identifies a set of candidate features based on the data characteristics and ...More

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